| Vagrant.configure("2") do |config| | |
| config.vm.define "microk8s" do |microk8s| | |
| microk8s.vm.box = "ubuntu/bionic64" | |
| microk8s.vm.hostname = "microk8s" | |
| microk8s.vm.network "forwarded_port", guest: 3000, host: 3000 | |
| microk8s.vm.network "forwarded_port", guest: 9090, host: 9090 | |
| microk8s.vm.network "forwarded_port", guest: 9070, host: 9070 |
This Virtual Machine (using Vagrant) to build an Ubuntu based virtual machine that has the MicroK8S setup of Kubernetes.
It also installs docker, and sets up aliases for kubectl in line with the MicroK8S documentation.
Initially this should be functionally similar to MiniKube.
If you want a multi-node similar environment, here's a similar repository.
05/22 - Deep Learning Hands-On Series - Data Exploration and API First Design 🎥
05/29 - Deep Learning Hands-On Series - Model Tuning 🎥
06/05 - Deep Learning Hands-On Series - Monitoring [cancelled]
AutoML is a very active area of AI research in academia as well as R&D work in industry. The public cloud vendors each promote some form of AutoML service. Tech unicorns have been developing AutoML services for their data platforms. Many different open source projects are available, which provide interesting new approaches. But what does AutoML mean?
Ostensibly automated machine learning will help put ML capabilities into the hands of non-experts, help improve the efficiency of ML workflows, and accelerate AI research overall. While in the long-term AutoML services promise to automate the end-to-end process of applying ML in real-world business use cases, what are the capabilities and limitations in the near-term?
Building and managing AI models is now becoming the key competency for application developers and software engineers. Collaborating with data scientists and ML engineers, the application and DevOps teams are gaining skills and becoming active participants for the AI lifecycle management. Powered by AutoAI from Watson AI technology, you can build models with Watson Studio, run models with Watson Machine Learning and measure models with Watson OpenScale.
| # | |
| # | |
| # main() will be run when you invoke this action | |
| # | |
| # @param Cloud Functions actions accept a single parameter, which must be a JSON object. | |
| # | |
| # @return The output of this action, which must be a JSON object. | |
| # | |
| # | |
| import sys |
| My message is that we'll be watching you. | |
| This is all wrong. I shouldn't be up here. I should be back in school on the other side of the ocean. Yet, you all come to us young people for hope. How dare you! | |
| You have stolen my dreams and my childhood with your empty words and yet I'm one of the lucky ones. People are suffering. People are dying. Entire ecosystems are collapsing. We are in the beginning of a mass extinction and all you can talk about is money and fairytales of eternal economic growth. How dare you! | |
| For more than 30 years, the science has been crystal clear. How dare you continue to look away and come here saying that you're doing enough when the politics and solutions needed are still nowhere in sight. | |
| You say you hear us and that you understand the urgency, but no matter how sad and angry I am, I do not want to believe that. Because if you really understood the situation and still kept on failing to act then you would be evil and that I refuse to believe. |
